Accelerating Raw Data Analysis with the ACCORDA Software and Hardware Architecture
Summary: ACCORDA: encoding-aware operator interfaces with a uniform runtime for raw data. UDP in memory accelerates parsing/decompression 16–21x and deserialization up to 160x, yielding 2.9x–13.2x speedups vs SparkSQL and ~80% gains from encoding-driven optimizations. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yuanwei Fang (University of Chicago)
- 2. Chen Zou (University of Chicago)
- 3. Andrew A. Chien (Argonne National Laboratory; University of Chicago)
BibTeX Citation
@article{fang_vldb19,
title = {{Accelerating Raw Data Analysis with the ACCORDA Software and Hardware Architecture}},
author = {Fang, Yuanwei and Zou, Chen and Chien, Andrew A.},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {11},
pages = {1568--1582},
doi = {10.14778/3342263.3342634},
url = {https://doi.org/10.14778/3342263.3342634},
year = {2019}
}
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,196 | Farview: Disaggregated Memory with Operator Off-loading for Database Engines | 2022 | CIDR | 7.6467469e-05 |
| 4,861 | CXL and the Return of Scale-Up Database Engines | 2024 | VLDB | 6.4747307e-05 |
| 5,622 | Good to the Last Bit: Data-Driven Encoding with CodecDB | 2021 | SIGMOD | 6.1461066e-05 |
| 7,899 | Modularis: Modular Relational Analytics over Heterogeneous Distributed Platforms | 2021 | VLDB | 5.5195553e-05 |
| 8,341 | Tackling Hardware/Software co-design from a database perspective | 2020 | CIDR | 5.4486102e-05 |
| 9,568 | Making Search Engines Faster by Lowering the Cost of Querying Business Rules Through FPGAs | 2020 | SIGMOD | 5.2528121e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 23 of 23 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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